code: def __init__(self) -> None:
      self._data = torch.rand((100, 100))
  
file_path: nni/test/algo/compression/distillation/test_distil_label_patcher.py
imports: from __future__ import annotations
  import hashlib
  import pytest
  import torch
  from torch.utils.data import Dataset, DataLoader
  from nni.contrib.distillation.label_patcher import DistilLabelPatcher
  from nni.contrib.distillation.uid_dataset import IndexedDataset, HashedDataset, AugmentationDataset
  from ..assets.common import log_dir
label_desc: Use image node_id 1 to create a new DemoDataset object from inherited base classes: Dataset with example: obj = DemoDataset()